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Updated: May 21, 2026

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes
Published on: March 28, 2025
Relative changes in genetic variability and correlations in an early-maturing maize population during recurrent
B Badu-Apraku1, R O Akinwale, M A B Fakorede
1International Institute of Tropical Agriculture (IITA), IITA Ltd, Carolyn House, 26 Dingwall Road, Croydon, CR9 3EE, UK. b.badu-apraku@cgiar.org
Recurrent selection improved maize grain yield and Striga resistance, showing adequate genetic variability for future gains. Realized gains were lower than predicted, indicating potential for further improvement in Striga-infested conditions.
Area of Science:
- Plant breeding and genetics
- Agronomy
- Crop science
Background:
- Recurrent selection is a breeding strategy to improve quantitative traits in crops.
- Striga hermonthica is a parasitic weed that significantly reduces maize grain yield in Africa.
- Evaluating genetic variance is crucial for the sustainability of breeding programs.
Purpose of the Study:
- To assess changes in genetic variance, heritability, and genetic correlations after four cycles of selection in maize.
- To predict future gains for grain yield and Striga resistance.
- To determine the viability of continuing the recurrent selection scheme.
Main Methods:
- Four cycles of S(1) family recurrent selection were applied to TZE-Y Pop STR C(0.) maize population.
- Fifty S(1) families from each cycle were evaluated under Striga-infested and Striga-free conditions in Nigeria.
- Genetic variances, heritability estimates, and genetic correlations were analyzed.
Main Results:
- Advanced selection cycles showed increased genetic variances for grain yield and Striga damage under infestation.
- Selected maize cycles significantly out-yielded the original cycle.
- Realized gains for grain yield were lower than predicted, but adequate genetic variability remains.
Conclusions:
- The recurrent selection scheme has generated substantial genetic gains for grain yield and Striga resistance.
- Residual genetic variance in cycle 4 supports continued selection for further improvement.
- Optimizing selection strategies may be needed to bridge the gap between predicted and realized gains.
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